We are seeking a skilled machine learning engineer (ML Eng) to join one of our agile development teams in our ML & AI ART.

Responsibilities

- Develop, deploy, and optimize machine learning and AI solutions that address complex business challenges.
- Create multi‑agent systems and equip AI models with function/tool‑calling capabilities.
- Design and implement Retrieval‑Augmented Generation (RAG) systems to ground AI responses in enterprise data.
- Assess and integrate AI models (e.g., LLMs) ensuring optimal performance and reliability.
- Optimize agentic workflows and AI agents for production use cases.
- Test and optimize system prompts and few‑shot examples to ensure accurate, consistent, and safe AI outputs.
- Perform performance evaluation of machine learning and AI models using appropriate metrics, evaluation sets and techniques, and continuously iterate and improve upon them.
- Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes.
- Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions.

Qualifications
- Strong problem‑solving and analytical skills, with the ability to think critically and creatively about complex challenges.
- Excellent communication and collaboration skills, enabling effective teamwork with cross‑functional stakeholders at all levels of the organization.
- Ability to manage personal workloads effectively, prioritize tasks, manage timelines,



and deliver high‑quality results on schedule.
- Continuous learning mindset, with a passion for staying up‑to‑date with the latest advancements in machine learning and artificial intelligence.
- Attention to detail and commitment to producing high‑quality, reliable, and maintainable code.
- Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Strong programming skills in Python with experience in machine learning libraries and deep learning frameworks such as TensorFlow or PyTorch.
- Proven experience working with Large Language Models (LLMs).
- Good understanding of AI agents & agentic workflows, LLM orchestration frameworks, and reasoning patterns.
- Experience with data preprocessing, feature engineering, and model selection and evaluation techniques.
- Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimisation.
- Understanding of software development best practices, including version control, testing, and documentation.
- Excellent problem‑solving and debugging skills, with the ability to identify and resolve issues quickly and effectively.
- Relevant work experience in machine learning, data science or a related field.
- Good English; Spanish is a plus.

Benefits
- Continuous learning opportunities and support for professional development.
- Adaptable working options.
- Wide array of health and well‑being benefits. xcskxlj
- Extensive career development programmes.

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📌 Machine Learning Engineer 100% (f/m/d) (Madrid)
🏢 Bank Julius Bär Ltd.
📍 Madrid